"Enhancing Lung Cancer Detection: A Comparative Analysis of CNN and RNN Models on X-Ray Image Data"

Lung cancer originates from abnormal growth in lung cells, characterized by uncontrolled cell division within lung tissues. Early detection of lung cancer is crucial for improving patient outcomes and survival rates. The cited papers highlight several limitations, such as small sample sizes, reliance on previous studies, the need for future validation, resource-intensive methods, potential biases, lack of longitudinal data, necessity for further experimentation, limited clinical practice integration, dependence on imaging quality, and insufficient data for robust model training and evaluation.

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Publication Details

Journal
Biomedical Journal of Scientific & Technical Research
Published
2024-08-20
DOI
https://doi.org/10.26717/bjstr.2024.58.009131
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

"Enhancing Lung Cancer Detection: A Comparative Analysis of CNN and RNN Models on X-Ray Image Data"

B. Sankar
1 links
Biomedical Journal of Scientific & Technical Research
Radiomics and Machine Learning in Medical Imaging
article

"Enhancing Lung Cancer Detection: A Comparative Analysis of CNN and RNN Models on X-Ray Image Data"

B. Sankar
article en

Abstract

Lung cancer originates from abnormal growth in lung cells, characterized by uncontrolled cell division within lung tissues. Early detection of lung cancer is crucial for improving patient outcomes and survival rates. The cited papers highlight several limitations, such as small sample sizes, reliance on previous studies, the need for future validation, resource-intensive methods, potential biases, lack of longitudinal data, necessity for further experimentation, limited clinical practice integration, dependence on imaging quality, and insufficient data for robust model training and evaluation.

Biomedical Journal of Scientific & Technical ResearchVol. 58(2)
Annamalai University (IN)
Good health and well-being
Openalex Percentile: Top 71%
Radiomics and Machine Learning in Medical Imaging
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